Xiao Luo
Papers
15
Total Citations
236
H-Index
8
About
Xiao Luo is a leading researcher in robot motion planning and control, whose work has fundamentally advanced how robots navigate complex, real-world environments. Luo’s primary contributions lie in developing novel algorithms for path planning, inverse kinematics, and trajectory control, with a particular focus on overcoming the challenges of high-dimensional spaces and narrow passages. Their most influential work, the improved Rapidly-exploring Random Tree (RRT) algorithm (73 citations), introduced a collision-free path planning method that has become a cornerstone for multi-degree-of-freedom manipulators. Luo also pioneered the Model Predictive Control with Integral Compensation (MPC-I) method (31 citations), which significantly enhances motion control accuracy by compensating for unmodeled dynamics. Further demonstrating their versatility, Luo designed the CMBOT, a biped climbing robot with a redundant manipulator for railway bridge inspection, and developed an optimized Probabilistic Roadmap algorithm (30 citations) for mobile robots in environments with narrow channels. With over 200 total citations across their publications, Luo’s work bridges theoretical innovation and practical application, making robots safer, more efficient, and capable of operating in the most constrained settings.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9Inverse Kinematics of Robot Manipulator Based on BODE-CS Algorithm8 citations · 2023
- 10